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Source code Book Forum Source code on GitHub Classic Computer Science Problems in Swift Slideshare: Learning Computer Science with Python Article: Constraint-Satisfaction Problems in Python Classic Computer Science Problems Interview: The Towers of Hanoi Register your pBook for a free eBook 🎙️ Podcast__Init 🎙️ David Kopec interviewed 🎙️ Constraint-Satisfaction Problems in Python 🎙️ Profitable Python with David Kopec 🎙️ Classic Computer Science Problems - David Kopec show all
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Classic Computer Science Problems in Python you own this product

David Kopec
  • March 2019
  • ISBN 9781617295980
  • 224 pages
  • printed in black & white
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Whether you're a novice or a seasoned professional, there's an Aha! moment in this book for everyone.

James Watson, Adaptive
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Classic Computer Science Problems in Python deepens your knowledge of problem solving techniques from the realm of computer science by challenging you with time-tested scenarios, exercises, and algorithms. As you work through examples in search, clustering, graphs, and more, you'll remember important things you've forgotten and discover classic solutions to your "new" problems!
This book is one of three products included in the Python Gymnasium bundle. Get the entire bundle for only $49.99.

about the technology

Computer science problems that seem new or unique are often rooted in classic algorithms, coding techniques, and engineering principles. And classic approaches are still the best way to solve them! Understanding these techniques in Python expands your potential for success in web development, data munging, machine learning, and more.

about the book

Classic Computer Science Problems in Python sharpens your CS problem-solving skills with time-tested scenarios, exercises, and algorithms, using Python. You'll tackle dozens of coding challenges, ranging from simple tasks like binary search algorithms to clustering data using k-means. You'll especially enjoy the feeling of satisfaction as you crack problems that connect computer science to the real-world concerns of apps, data, performance, and even nailing your next job interview!

what's inside

  • Search algorithms
  • Common techniques for graphs
  • Neural networks
  • Genetic algorithms
  • Adversarial search
  • Uses type hints throughout
  • Covers Python 3.7

about the reader

For intermediate Python programmers.

about the author

David Kopec is an assistant professor of Computer Science and Innovation at Champlain College in Burlington, Vermont. He is the author of Dart for Absolute Beginners (Apress, 2014) and Classic Computer Science Problems in Swift (Manning, 2018).

We interviewed David as a part of our Six Questions series. Check it out here.

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A fun way to get hands-on experience with classical computer science problems in modern Python.

Jens Christian Bredahl Madsen, IT Relation

Highly recommended to everyone who is interested in deepening their understanding, not only of the Python language, but also of practical computer science.

Daniel Kenney-Jung, MD, University of Minnesota

Classic problems presented in a wonderfully entertaining way with a language that always seems to have something new to offer.

Sam Zaydel, RackTop Systems

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